We find the orignal information here.

Introduction

This report and analysis on Seattle’s bicycle sharing trends. The data includes weather reports for the area, the station locations, and trips taken by cycle riders. Future explorations could include the addition of other forms of public transportation for the Seatle area to better understand commuter travel trends.

Station Locations

Lets take a look at where the rental stations are located in Seattle!

##   n_distinct(install_date)
## 1                        9
## # A tibble: 9 x 2
##   install_date count
##         <date> <int>
## 1   2014-10-13    50
## 2   2015-05-22     1
## 3   2015-06-12     1
## 4   2015-07-27     1
## 5   2015-09-15     1
## 6   2015-10-29     1
## 7   2016-03-18     1
## 8   2016-07-03     1
## 9   2016-08-09     1
##   n_distinct(station_id)
## 1                     58
## note : locations should be specified in the lon/lat format, not lat/lon.
## Map from URL : http://maps.googleapis.com/maps/api/staticmap?center=47.6,-122.35&zoom=12&size=640x640&scale=2&maptype=roadmap&language=en-EN&sensor=false

closeUp <- get_map(location = "Seattle", maptype = "roadmap", zoom = 13)

# Plot a single point for each Station ID
ggmap(closeUp) + geom_point(aes(x = long, y = lat), data = station_locs, 
                            alpha = 1, color = "darkred", size = 3)
Stations map Zoomed In

Stations map Zoomed In

Look at all those stations!

Histogram of Number of Bikes per Station

Current Dock Count

Current Dock Count

Here is a histogram of the number of bikes per station.

Change in Number of Bike Docks Per Station

Change in Number of Bike Docks Per Station

Here is a map of how many times dock changed occured per station.

Current Station Size

Current Station Size

11 stations lost bike docks, 39 docks stayed the same, 8 stations gained docks.

Time to visualize the number of rides per day

Time to visualize the number of rides per day

Plotting trips per month (by season, minus summer)

Trips Per Month (By Season)

Trips Per Month (By Season)

Convert Trip Duration from Seconds to Minutes

Average Trip Duration

Average Trip Duration

Number of Trips by Day of Week

Number of Trips Per Time of Day

Number of Trips by Member Type

Trip Duration by Member Type

Member Demographics

## 'data.frame':    689 obs. of  21 variables:
##  $ Date                      : chr  "10/13/2014" "10/14/2014" "10/15/2014" "10/16/2014" ...
##  $ Max_Temperature_F         : int  71 63 62 71 64 68 73 66 64 60 ...
##  $ Mean_Temperature_F        : int  62 59 58 61 60 64 64 60 58 58 ...
##  $ Min_TemperatureF          : int  54 55 54 52 57 59 55 55 55 57 ...
##  $ Max_Dew_Point_F           : int  55 52 53 49 55 59 57 57 52 55 ...
##  $ MeanDew_Point_F           : int  51 51 50 46 51 57 55 54 49 53 ...
##  $ Min_Dewpoint_F            : int  46 50 46 42 41 55 53 50 46 48 ...
##  $ Max_Humidity              : int  87 88 87 83 87 90 94 90 87 88 ...
##  $ Mean_Humidity             : int  68 78 77 61 72 83 74 78 70 81 ...
##  $ Min_Humidity              : int  46 63 67 36 46 68 52 67 58 67 ...
##  $ Max_Sea_Level_Pressure_In : num  30 29.8 30 30 29.8 ...
##  $ Mean_Sea_Level_Pressure_In: num  29.8 29.8 29.7 29.9 29.8 ...
##  $ Min_Sea_Level_Pressure_In : num  29.6 29.5 29.5 29.8 29.7 ...
##  $ Max_Visibility_Miles      : int  10 10 10 10 10 10 10 10 10 10 ...
##  $ Mean_Visibility_Miles     : int  10 9 9 10 10 8 10 10 10 6 ...
##  $ Min_Visibility_Miles      : int  4 3 3 10 6 2 6 5 6 2 ...
##  $ Max_Wind_Speed_MPH        : int  13 10 18 9 8 10 10 12 15 14 ...
##  $ Mean_Wind_Speed_MPH       : int  4 5 7 4 3 4 3 5 8 8 ...
##  $ Max_Gust_Speed_MPH        : chr  "21" "17" "25" "-" ...
##  $ Precipitation_In          : num  0 0.11 0.45 0 0.14 0.31 0 0.44 0.1 1.43 ...
##  $ Events                    : chr  "Rain" "Rain" "Rain" "Rain" ...
##  [1] ""                    "Fog"                 "Fog , Rain"         
##  [4] "Fog-Rain"            "Rain"                "Rain , Snow"        
##  [7] "Rain , Thunderstorm" "Rain-Snow"           "Rain-Thunderstorm"  
## [10] "Snow"
## [1] "2016-02-14"

Mean Temps

Max Temps

Events

## 'data.frame':    689 obs. of  21 variables:
##  $ Date                      : Date, format: "2014-10-13" "2014-10-14" ...
##  $ Max_Temperature_F         : int  71 63 62 71 64 68 73 66 64 60 ...
##  $ Mean_Temperature_F        : num  62 59 58 61 60 64 64 60 58 58 ...
##  $ Min_TemperatureF          : int  54 55 54 52 57 59 55 55 55 57 ...
##  $ Max_Dew_Point_F           : int  55 52 53 49 55 59 57 57 52 55 ...
##  $ MeanDew_Point_F           : int  51 51 50 46 51 57 55 54 49 53 ...
##  $ Min_Dewpoint_F            : int  46 50 46 42 41 55 53 50 46 48 ...
##  $ Max_Humidity              : int  87 88 87 83 87 90 94 90 87 88 ...
##  $ Mean_Humidity             : int  68 78 77 61 72 83 74 78 70 81 ...
##  $ Min_Humidity              : int  46 63 67 36 46 68 52 67 58 67 ...
##  $ Max_Sea_Level_Pressure_In : num  30 29.8 30 30 29.8 ...
##  $ Mean_Sea_Level_Pressure_In: num  29.8 29.8 29.7 29.9 29.8 ...
##  $ Min_Sea_Level_Pressure_In : num  29.6 29.5 29.5 29.8 29.7 ...
##  $ Max_Visibility_Miles      : int  10 10 10 10 10 10 10 10 10 10 ...
##  $ Mean_Visibility_Miles     : int  10 9 9 10 10 8 10 10 10 6 ...
##  $ Min_Visibility_Miles      : int  4 3 3 10 6 2 6 5 6 2 ...
##  $ Max_Wind_Speed_MPH        : int  13 10 18 9 8 10 10 12 15 14 ...
##  $ Mean_Wind_Speed_MPH       : int  4 5 7 4 3 4 3 5 8 8 ...
##  $ Max_Gust_Speed_MPH        : num  21 17 25 0 0 0 18 0 21 22 ...
##  $ Precipitation_In          : num  0 0.11 0.45 0 0.14 0.31 0 0.44 0.1 1.43 ...
##  $ Events                    : Factor w/ 7 levels "Fog","Fog-Rain",..: 4 4 4 4 4 4 3 4 4 4 ...

Mean Temperature vs. Number of Trips

Normalize

Precipitation vs. Number of Trips